Retention and Excretion of Inhaled 3H and 14C Radiolabeled Methane in Rats
Bibliographic record
Abstract
A radiological concern for workers at heavy water reactor nuclear facilities is the hazard presented by tritium (H) and C. Radioactive methane is one of many potential H and C containing chemicals to which Nuclear Energy Workers (NEWs) may be exposed. Current dosimetric models for H- and C-methane, recommended by the International Commission on Radiological Protection (ICRP), are based on the assumption that 1% of methane is absorbed following its inhalation. Of this 1%, all H is converted immediately to tritiated water and C is converted immediately to CO2 (50%) and organically bound carbon (50%). In the study, rats were exposed to methane standards (H-methane and C-methane) mixed with breathing air to give a final concentration of 0.27% methane and resulting in final activity concentrations of 4.2 GBq m and 0.88 GBq m for H and C, respectively. This corresponds to exposure estimates of 580 kBq g and 120 kBq g. Simultaneous exposure to H- and C-methane allowed for the direct comparison of the retention of these radionuclides and removed uncertainties concerning their relative uptake and retention. The results demonstrate that the total methane uptake from the inhaled dose was threefold less than the 1% methane uptake predicted by the ICRP dosimetric models for H- and C-methane, with the H concentration being substantially higher than anticipated in the liver. This study provided data suggesting that current ICRP dosimetric methane models overestimate the fraction of H- and C-methane that is absorbed following inhalation and assisted in providing information to better understand the metabolism of inhaled H and C radiolabeled methane.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".